Optimization of Risk Weighted Assets: Algorithms and Insights

In the wake of the 2008 global financial crisis, the Basel III Accord imposed minimum capital requirements to strengthen the resilience of individual banks and thus enhance the stability of the international financial system. This in turn elevated the need to properly assess the banks risk-weighted assets, RWA. The case describes the evolution of approaches to calculating RWA for a certain class of assets at one of the largest banks in Europe, and presents a sample dataset from one of its subsidiaries on which students can practice implementing them. The case is suitable for instructors who want to expose students taking advanced analytics courses to the topics of linear and interger optimization and the related heuristics in a large-scale, big-impact problem setting.

Provide an example of the use of advanced optimization in financial services. Expose students to linear and interger optimization and the related heuristics in a large-scale, big-impact problem setting, starting with a simple, easy-to-understand example. Explore multiple linear and integer programming approaches to a given problem, and discuss how the solvability of a real and computationally challenging problem can be significantly impacted by the creativity of the approach. Present an example of “beyond Excel” optimization with the sample Python code provided that utilizes a Gurobi solver. [Note: instructors and students can obtain educational Gurobi licenses at no cost].